Pandas Profiling Report

Dataset statistics

Number of variables	24
Number of observations	30000
Missing cells	25062
Missing cells (%)	3.5%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	5.5 MiB
Average record size in memory	192.0 B

Variable types

Categorical	12
Numeric	10
Boolean	2

Warnings

`Customer ID` has a high cardinality: 30000 distinct values	High cardinality
`Name` has a high cardinality: 30000 distinct values	High cardinality
`Income (USD)` is highly correlated with `Property Age`	High correlation
`Loan Amount Request (USD)` is highly correlated with `Current Loan Expenses (USD)` and 2 other fields	High correlation
`Current Loan Expenses (USD)` is highly correlated with `Loan Amount Request (USD)` and 1 other fields	High correlation
`Property Age` is highly correlated with `Income (USD)`	High correlation
`Property Price` is highly correlated with `Loan Amount Request (USD)` and 2 other fields	High correlation
`Loan Sanction Amount (USD)` is highly correlated with `Loan Amount Request (USD)` and 1 other fields	High correlation
`Income (USD)` is highly correlated with `Property Age`	High correlation
`Loan Amount Request (USD)` is highly correlated with `Current Loan Expenses (USD)` and 2 other fields	High correlation
`Current Loan Expenses (USD)` is highly correlated with `Loan Amount Request (USD)` and 1 other fields	High correlation
`Property Age` is highly correlated with `Income (USD)`	High correlation
`Property Price` is highly correlated with `Loan Amount Request (USD)` and 2 other fields	High correlation
`Loan Sanction Amount (USD)` is highly correlated with `Loan Amount Request (USD)` and 1 other fields	High correlation
`Income (USD)` is highly correlated with `Property Age`	High correlation
`Loan Amount Request (USD)` is highly correlated with `Current Loan Expenses (USD)` and 2 other fields	High correlation
`Current Loan Expenses (USD)` is highly correlated with `Loan Amount Request (USD)` and 1 other fields	High correlation
`Property Age` is highly correlated with `Income (USD)`	High correlation
`Property Price` is highly correlated with `Loan Amount Request (USD)` and 1 other fields	High correlation
`Loan Sanction Amount (USD)` is highly correlated with `Loan Amount Request (USD)`	High correlation
`Income Stability` is highly correlated with `Age` and 1 other fields	High correlation
`Current Loan Expenses (USD)` is highly correlated with `Loan Sanction Amount (USD)` and 2 other fields	High correlation
`Loan Sanction Amount (USD)` is highly correlated with `Current Loan Expenses (USD)` and 2 other fields	High correlation
`Income (USD)` is highly correlated with `Property Age`	High correlation
`Property Price` is highly correlated with `Current Loan Expenses (USD)` and 2 other fields	High correlation
`Age` is highly correlated with `Income Stability`	High correlation
`Profession` is highly correlated with `Income Stability`	High correlation
`Property Age` is highly correlated with `Income (USD)`	High correlation
`Loan Amount Request (USD)` is highly correlated with `Current Loan Expenses (USD)` and 2 other fields	High correlation
`Income Stability` is highly correlated with `Type of Employment` and 1 other fields	High correlation
`Type of Employment` is highly correlated with `Income Stability`	High correlation
`Profession` is highly correlated with `Income Stability`	High correlation
`Income (USD)` has 4576 (15.3%) missing values	Missing
`Income Stability` has 1683 (5.6%) missing values	Missing
`Type of Employment` has 7270 (24.2%) missing values	Missing
`Dependents` has 2493 (8.3%) missing values	Missing
`Credit Score` has 1703 (5.7%) missing values	Missing
`Has Active Credit Card` has 1566 (5.2%) missing values	Missing
`Property Age` has 4850 (16.2%) missing values	Missing
`Property Location` has 356 (1.2%) missing values	Missing
`Loan Sanction Amount (USD)` has 340 (1.1%) missing values	Missing
`Income (USD)` is highly skewed (γ1 = 154.00172)	Skewed
`Property Age` is highly skewed (γ1 = 153.2196101)	Skewed
`Customer ID` is uniformly distributed	Uniform
`Name` is uniformly distributed	Uniform
`Customer ID` has unique values	Unique
`Name` has unique values	Unique
`Loan Sanction Amount (USD)` has 7865 (26.2%) zeros	Zeros

Reproduction

Analysis started	2021-06-27 06:18:31.349608
Analysis finished	2021-06-27 06:19:32.772486
Duration	1 minute and 1.42 second
Software version	pandas-profiling v3.0.0
Download configuration	config.json

Customer ID
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	30000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

C-14537	1
C-27652	1
C-3942	1
C-5210	1
C-21819	1
Other values (29995)	29995

Length

Max length	7
Median length	7
Mean length	6.7817
Min length	3

Characters and Unicode

Total characters	203451
Distinct characters	12
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	30000 ?
Unique (%)	100.0%

Sample

1st row	C-36995
2nd row	C-33999
3rd row	C-3770
4th row	C-26480
5th row	C-23459

Common Values

Value	Count	Frequency (%)
C-14537	1	< 0.1%
C-27652	1	< 0.1%
C-3942	1	< 0.1%
C-5210	1	< 0.1%
C-21819	1	< 0.1%
C-37518	1	< 0.1%
C-10686	1	< 0.1%
C-16899	1	< 0.1%
C-47213	1	< 0.1%
C-11941	1	< 0.1%
Other values (29990)	29990	> 99.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
c-23326	1	< 0.1%
c-22306	1	< 0.1%
c-49252	1	< 0.1%
c-18314	1	< 0.1%
c-31781	1	< 0.1%
c-28221	1	< 0.1%
c-40106	1	< 0.1%
c-47617	1	< 0.1%
c-47062	1	< 0.1%
c-5234	1	< 0.1%
Other values (29990)	29990	> 99.9%

Most occurring characters

Value	Count	Frequency (%)
C	30000	14.7%
-	30000	14.7%
3	18132	8.9%
1	18078	8.9%
2	18076	8.9%
4	18055	8.9%
7	12108	6.0%
8	11965	5.9%
9	11955	5.9%
5	11888	5.8%
Other values (2)	23194	11.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	143451	70.5%
Uppercase Letter	30000	14.7%
Dash Punctuation	30000	14.7%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	18132	12.6%
1	18078	12.6%
2	18076	12.6%
4	18055	12.6%
7	12108	8.4%
8	11965	8.3%
9	11955	8.3%
5	11888	8.3%
6	11851	8.3%
0	11343	7.9%

Uppercase Letter

Value	Count	Frequency (%)
C	30000	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	30000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	173451	85.3%
Latin	30000	14.7%

Most frequent character per script

Common

Value	Count	Frequency (%)
-	30000	17.3%
3	18132	10.5%
1	18078	10.4%
2	18076	10.4%
4	18055	10.4%
7	12108	7.0%
8	11965	6.9%
9	11955	6.9%
5	11888	6.9%
6	11851	6.8%

Latin

Value	Count	Frequency (%)
C	30000	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	203451	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
C	30000	14.7%
-	30000	14.7%
3	18132	8.9%
1	18078	8.9%
2	18076	8.9%
4	18055	8.9%
7	12108	6.0%
8	11965	5.9%
9	11955	5.9%
5	11888	5.8%
Other values (2)	23194	11.4%

Name
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	30000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

Armida Lajeunesse	1
Lacey Devenport	1
Pamula Sackett	1
Maricela Brwon	1
Darlena Omalley	1
Other values (29995)	29995

Length

Max length	24
Median length	13
Mean length	13.52893333
Min length	6

Characters and Unicode

Total characters	405868
Distinct characters	53
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	30000 ?
Unique (%)	100.0%

Sample

1st row	Frederica Shealy
2nd row	America Calderone
3rd row	Rosetta Verne
4th row	Zoe Chitty
5th row	Afton Venema

Common Values

Value	Count	Frequency (%)
Armida Lajeunesse	1	< 0.1%
Lacey Devenport	1	< 0.1%
Pamula Sackett	1	< 0.1%
Maricela Brwon	1	< 0.1%
Darlena Omalley	1	< 0.1%
Genie Antoine	1	< 0.1%
Glendora Calender	1	< 0.1%
Margareta Koffler	1	< 0.1%
Roxy Teamer	1	< 0.1%
Nakita Marro	1	< 0.1%
Other values (29990)	29990	> 99.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
gina	113	0.2%
sidney	106	0.2%
teri	102	0.2%
lorriane	102	0.2%
jenni	100	0.2%
noe	100	0.2%
selena	99	0.2%
margareta	98	0.2%
desire	98	0.2%
brian	97	0.2%
Other values (2493)	58985	98.3%

Most occurring characters

Value	Count	Frequency (%)
e	44455	11.0%
a	40934	10.1%
	30000	7.4%
n	29296	7.2%
r	27736	6.8%
i	26855	6.6%
l	24035	5.9%
o	20028	4.9%
t	14824	3.7%
s	13009	3.2%
Other values (43)	134696	33.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	315868	77.8%
Uppercase Letter	60000	14.8%
Space Separator	30000	7.4%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
S	5846	9.7%
M	5481	9.1%
L	4541	7.6%
B	4139	6.9%
A	3989	6.6%
C	3862	6.4%
D	3206	5.3%
K	3163	5.3%
G	2844	4.7%
R	2721	4.5%
Other values (16)	20208	33.7%

Lowercase Letter

Value	Count	Frequency (%)
e	44455	14.1%
a	40934	13.0%
n	29296	9.3%
r	27736	8.8%
i	26855	8.5%
l	24035	7.6%
o	20028	6.3%
t	14824	4.7%
s	13009	4.1%
d	9474	3.0%
Other values (16)	65222	20.6%

Space Separator

Value	Count	Frequency (%)
	30000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	375868	92.6%
Common	30000	7.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	44455	11.8%
a	40934	10.9%
n	29296	7.8%
r	27736	7.4%
i	26855	7.1%
l	24035	6.4%
o	20028	5.3%
t	14824	3.9%
s	13009	3.5%
d	9474	2.5%
Other values (42)	125222	33.3%

Common

Value	Count	Frequency (%)
	30000	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	405868	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	44455	11.0%
a	40934	10.1%
	30000	7.4%
n	29296	7.2%
r	27736	6.8%
i	26855	6.6%
l	24035	5.9%
o	20028	4.9%
t	14824	3.7%
s	13009	3.2%
Other values (43)	134696	33.2%

Gender
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	53
Missing (%)	0.2%
Memory size	234.5 KiB

M	15053
F	14894

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	29947
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	F
2nd row	M
3rd row	F
4th row	F
5th row	F

Common Values

Value	Count	Frequency (%)
M	15053	50.2%
F	14894	49.6%
(Missing)	53	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
m	15053	50.3%
f	14894	49.7%

Most occurring characters

Value	Count	Frequency (%)
M	15053	50.3%
F	14894	49.7%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	29947	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
M	15053	50.3%
F	14894	49.7%

Most occurring scripts

Value	Count	Frequency (%)
Latin	29947	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
M	15053	50.3%
F	14894	49.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	29947	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
M	15053	50.3%
F	14894	49.7%

Age
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	48
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	40.0923

Minimum	18
Maximum	65
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	18
5-th percentile	18
Q1	25
median	40
Q3	55
95-th percentile	64
Maximum	65
Range	47
Interquartile range (IQR)	30

Descriptive statistics

Standard deviation	16.04512893
Coefficient of variation (CV)	0.4002047507
Kurtosis	-1.382082938
Mean	40.0923
Median Absolute Deviation (MAD)	15
Skewness	0.0460938016
Sum	1202769
Variance	257.4461622
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=48)

Value	Count	Frequency (%)
18	4378	14.6%
65	1349	4.5%
64	813	2.7%
61	787	2.6%
62	784	2.6%
60	774	2.6%
63	712	2.4%
57	538	1.8%
47	536	1.8%
44	523	1.7%
Other values (38)	18806	62.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
18	4378	14.6%
19	482	1.6%
20	499	1.7%
21	510	1.7%
22	469	1.6%
23	520	1.7%
24	503	1.7%
25	470	1.6%
26	513	1.7%
27	511	1.7%

Value	Count	Frequency (%)
65	1349	4.5%
64	813	2.7%
63	712	2.4%
62	784	2.6%
61	787	2.6%
60	774	2.6%
59	492	1.6%
58	514	1.7%
57	538	1.8%
56	507	1.7%

Income (USD)
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	24429
Distinct (%)	96.1%
Missing	4576
Missing (%)	15.3%
Infinite	0
Infinite (%)	0.0%
Mean	2630.574417

Minimum	377.7
Maximum	1777460.21
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	377.7
5-th percentile	1034.6115
Q1	1650.4575
median	2222.435
Q3	3090.5925
95-th percentile	5071.825
Maximum	1777460.21
Range	1777082.51
Interquartile range (IQR)	1440.135

Descriptive statistics

Standard deviation	11262.72383
Coefficient of variation (CV)	4.281469384
Kurtosis	24259.66896
Mean	2630.574417
Median Absolute Deviation (MAD)	663.2
Skewness	154.00172
Sum	66879723.99
Variance	126848948.1
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2415.7	4	< 0.1%
1608.43	4	< 0.1%
1723.73	3	< 0.1%
2206.6	3	< 0.1%
1868.78	3	< 0.1%
2304.81	3	< 0.1%
1617.97	3	< 0.1%
1282.74	3	< 0.1%
1681.48	3	< 0.1%
2412.07	3	< 0.1%
Other values (24419)	25392	84.6%
(Missing)	4576	15.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
377.7	1	< 0.1%
378.76	1	< 0.1%
378.91	1	< 0.1%
393.09	1	< 0.1%
418.9	1	< 0.1%
424.45	1	< 0.1%
437.63	1	< 0.1%
438.44	1	< 0.1%
442.47	1	< 0.1%
450.16	1	< 0.1%

Value	Count	Frequency (%)
1777460.21	1	< 0.1%
122966.28	1	< 0.1%
54653.75	1	< 0.1%
48095.16	1	< 0.1%
32726.98	1	< 0.1%
31866.97	1	< 0.1%
31584.05	1	< 0.1%
28331.74	1	< 0.1%
27518.64	1	< 0.1%
26049.85	1	< 0.1%

Income Stability
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	< 0.1%
Missing	1683
Missing (%)	5.6%
Memory size	234.5 KiB

Low	25751
High	2566

Length

Max length	4
Median length	3
Mean length	3.090616944
Min length	3

Characters and Unicode

Total characters	87517
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Low
2nd row	Low
3rd row	High
4th row	High
5th row	Low

Common Values

Value	Count	Frequency (%)
Low	25751	85.8%
High	2566	8.6%
(Missing)	1683	5.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
low	25751	90.9%
high	2566	9.1%

Most occurring characters

Value	Count	Frequency (%)
L	25751	29.4%
o	25751	29.4%
w	25751	29.4%
H	2566	2.9%
i	2566	2.9%
g	2566	2.9%
h	2566	2.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	59200	67.6%
Uppercase Letter	28317	32.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	25751	43.5%
w	25751	43.5%
i	2566	4.3%
g	2566	4.3%
h	2566	4.3%

Uppercase Letter

Value	Count	Frequency (%)
L	25751	90.9%
H	2566	9.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	87517	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
L	25751	29.4%
o	25751	29.4%
w	25751	29.4%
H	2566	2.9%
i	2566	2.9%
g	2566	2.9%
h	2566	2.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	87517	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
L	25751	29.4%
o	25751	29.4%
w	25751	29.4%
H	2566	2.9%
i	2566	2.9%
g	2566	2.9%
h	2566	2.9%

Profession
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

Working	16926
Commercial associate	7962
Pensioner	2740
State servant	2366
Unemployed	2
Other values (3)	4

Length

Max length	20
Median length	7
Mean length	11.1068
Min length	7

Characters and Unicode

Total characters	333204
Distinct characters	26
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	< 0.1%

Sample

1st row	Working
2nd row	Working
3rd row	Pensioner
4th row	Pensioner
5th row	Working

Common Values

Value	Count	Frequency (%)
Working	16926	56.4%
Commercial associate	7962	26.5%
Pensioner	2740	9.1%
State servant	2366	7.9%
Unemployed	2	< 0.1%
Businessman	2	< 0.1%
Student	1	< 0.1%
Maternity leave	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
working	16926	42.0%
commercial	7962	19.7%
associate	7962	19.7%
pensioner	2740	6.8%
servant	2366	5.9%
state	2366	5.9%
unemployed	2	< 0.1%
businessman	2	< 0.1%
student	1	< 0.1%
maternity	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
i	35593	10.7%
o	35592	10.7%
r	29995	9.0%
a	28622	8.6%
e	26146	7.8%
n	24780	7.4%
s	21036	6.3%
W	16926	5.1%
k	16926	5.1%
g	16926	5.1%
Other values (16)	80662	24.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	292875	87.9%
Uppercase Letter	30000	9.0%
Space Separator	10329	3.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
i	35593	12.2%
o	35592	12.2%
r	29995	10.2%
a	28622	9.8%
e	26146	8.9%
n	24780	8.5%
s	21036	7.2%
k	16926	5.8%
g	16926	5.8%
m	15928	5.4%
Other values (8)	41331	14.1%

Uppercase Letter

Value	Count	Frequency (%)
W	16926	56.4%
C	7962	26.5%
P	2740	9.1%
S	2367	7.9%
U	2	< 0.1%
B	2	< 0.1%
M	1	< 0.1%

Space Separator

Value	Count	Frequency (%)
	10329	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	322875	96.9%
Common	10329	3.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
i	35593	11.0%
o	35592	11.0%
r	29995	9.3%
a	28622	8.9%
e	26146	8.1%
n	24780	7.7%
s	21036	6.5%
W	16926	5.2%
k	16926	5.2%
g	16926	5.2%
Other values (15)	70333	21.8%

Common

Value	Count	Frequency (%)
	10329	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	333204	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
i	35593	10.7%
o	35592	10.7%
r	29995	9.0%
a	28622	8.6%
e	26146	7.8%
n	24780	7.4%
s	21036	6.3%
W	16926	5.1%
k	16926	5.1%
g	16926	5.1%
Other values (16)	80662	24.2%

Type of Employment
Categorical

HIGH CORRELATION
MISSING

Distinct	18
Distinct (%)	0.1%
Missing	7270
Missing (%)	24.2%
Memory size	234.5 KiB

Laborers	5578
Sales staff	3736
Core staff	3230
Managers	2495
Drivers	1606
Other values (13)	6085

Length

Max length	21
Median length	10
Mean length	10.61728993
Min length	7

Characters and Unicode

Total characters	241331
Distinct characters	36
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Sales staff
2nd row	High skill tech staff
3rd row	Secretaries
4th row	Laborers
5th row	Managers

Common Values

Value	Count	Frequency (%)
Laborers	5578	18.6%
Sales staff	3736	12.5%
Core staff	3230	10.8%
Managers	2495	8.3%
Drivers	1606	5.4%
Accountants	1379	4.6%
High skill tech staff	1307	4.4%
Medicine staff	864	2.9%
Security staff	579	1.9%
Cooking staff	566	1.9%
Other values (8)	1390	4.6%
(Missing)	7270	24.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
staff	11263	30.3%
laborers	5740	15.4%
sales	3736	10.0%
core	3230	8.7%
managers	2495	6.7%
drivers	1606	4.3%
accountants	1379	3.7%
skill	1307	3.5%
tech	1307	3.5%
high	1307	3.5%
Other values (13)	3827	10.3%

Most occurring characters

Value	Count	Frequency (%)
s	28426	11.8%
a	28422	11.8%
e	22741	9.4%
f	22526	9.3%
r	22300	9.2%
t	16731	6.9%
	14467	6.0%
o	11643	4.8%
i	8590	3.6%
n	7600	3.1%
Other values (26)	57885	24.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	203512	84.3%
Uppercase Letter	23041	9.5%
Space Separator	14467	6.0%
Dash Punctuation	162	0.1%
Other Punctuation	149	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
s	28426	14.0%
a	28422	14.0%
e	22741	11.2%
f	22526	11.1%
r	22300	11.0%
t	16731	8.2%
o	11643	5.7%
i	8590	4.2%
n	7600	3.7%
l	7101	3.5%
Other values (11)	27432	13.5%

Uppercase Letter

Value	Count	Frequency (%)
L	5902	25.6%
S	4476	19.4%
C	4137	18.0%
M	3359	14.6%
D	1606	7.0%
H	1379	6.0%
A	1379	6.0%
P	342	1.5%
R	158	0.7%
W	149	0.6%
Other values (2)	154	0.7%

Space Separator

Value	Count	Frequency (%)
	14467	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	149	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	162	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	226553	93.9%
Common	14778	6.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
s	28426	12.5%
a	28422	12.5%
e	22741	10.0%
f	22526	9.9%
r	22300	9.8%
t	16731	7.4%
o	11643	5.1%
i	8590	3.8%
n	7600	3.4%
l	7101	3.1%
Other values (23)	50473	22.3%

Common

Value	Count	Frequency (%)
	14467	97.9%
-	162	1.1%
/	149	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	241331	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
s	28426	11.8%
a	28422	11.8%
e	22741	9.4%
f	22526	9.3%
r	22300	9.2%
t	16731	6.9%
	14467	6.0%
o	11643	4.8%
i	8590	3.6%
n	7600	3.1%
Other values (26)	57885	24.0%

Location
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

Semi-Urban	21563
Rural	5338
Urban	3099

Length

Max length	10
Median length	10
Mean length	8.593833333
Min length	5

Characters and Unicode

Total characters	257815
Distinct characters	13
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Semi-Urban
2nd row	Semi-Urban
3rd row	Semi-Urban
4th row	Rural
5th row	Semi-Urban

Common Values

Value	Count	Frequency (%)
Semi-Urban	21563	71.9%
Rural	5338	17.8%
Urban	3099	10.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
semi-urban	21563	71.9%
rural	5338	17.8%
urban	3099	10.3%

Most occurring characters

Value	Count	Frequency (%)
r	30000	11.6%
a	30000	11.6%
U	24662	9.6%
b	24662	9.6%
n	24662	9.6%
S	21563	8.4%
e	21563	8.4%
m	21563	8.4%
i	21563	8.4%
-	21563	8.4%
Other values (3)	16014	6.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	184689	71.6%
Uppercase Letter	51563	20.0%
Dash Punctuation	21563	8.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	30000	16.2%
a	30000	16.2%
b	24662	13.4%
n	24662	13.4%
e	21563	11.7%
m	21563	11.7%
i	21563	11.7%
u	5338	2.9%
l	5338	2.9%

Uppercase Letter

Value	Count	Frequency (%)
U	24662	47.8%
S	21563	41.8%
R	5338	10.4%

Dash Punctuation

Value	Count	Frequency (%)
-	21563	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	236252	91.6%
Common	21563	8.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	30000	12.7%
a	30000	12.7%
U	24662	10.4%
b	24662	10.4%
n	24662	10.4%
S	21563	9.1%
e	21563	9.1%
m	21563	9.1%
i	21563	9.1%
R	5338	2.3%
Other values (2)	10676	4.5%

Common

Value	Count	Frequency (%)
-	21563	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	257815	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	30000	11.6%
a	30000	11.6%
U	24662	9.6%
b	24662	9.6%
n	24662	9.6%
S	21563	8.4%
e	21563	8.4%
m	21563	8.4%
i	21563	8.4%
-	21563	8.4%
Other values (3)	16014	6.2%

Loan Amount Request (USD)
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	29982
Distinct (%)	99.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	88826.33386

Minimum	6048.24
Maximum	621497.82
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	6048.24
5-th percentile	21009.856
Q1	41177.755
median	75128.075
Q3	119964.605
95-th percentile	203686.565
Maximum	621497.82
Range	615449.58
Interquartile range (IQR)	78786.85

Descriptive statistics

Standard deviation	59536.9496
Coefficient of variation (CV)	0.6702623763
Kurtosis	2.103379537
Mean	88826.33386
Median Absolute Deviation (MAD)	36681.98
Skewness	1.260392183
Sum	2664790016
Variance	3544648368
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
70410.47	2	< 0.1%
81346.59	2	< 0.1%
30810.81	2	< 0.1%
20323.29	2	< 0.1%
68353.33	2	< 0.1%
73908.66	2	< 0.1%
115859.9	2	< 0.1%
60315.37	2	< 0.1%
101644.5	2	< 0.1%
43921.71	2	< 0.1%
Other values (29972)	29980	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
6048.24	1	< 0.1%
6108.05	1	< 0.1%
6145.01	1	< 0.1%
6174.7	1	< 0.1%
6189.5	1	< 0.1%
6307.15	1	< 0.1%
6310.26	1	< 0.1%
6341.02	1	< 0.1%
6431.37	1	< 0.1%
6436.14	1	< 0.1%

Value	Count	Frequency (%)
621497.82	1	< 0.1%
602384.15	1	< 0.1%
564812.49	1	< 0.1%
447860.56	1	< 0.1%
417936.91	1	< 0.1%
417580.72	1	< 0.1%
412229.23	1	< 0.1%
408413.2	1	< 0.1%
401084.8	1	< 0.1%
398662.89	1	< 0.1%

Current Loan Expenses (USD)
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	24041
Distinct (%)	80.6%
Missing	172
Missing (%)	0.6%
Infinite	0
Infinite (%)	0.0%
Mean	400.9368764

Minimum	-999
Maximum	3840.88
Zeros	0
Zeros (%)	0.0%
Negative	177
Negative (%)	0.6%
Memory size	234.5 KiB

Quantile statistics

Minimum	-999
5-th percentile	127.3635
Q1	247.6675
median	375.205
Q3	521.2925
95-th percentile	799.7755
Maximum	3840.88
Range	4839.88
Interquartile range (IQR)	273.625

Descriptive statistics

Standard deviation	242.5453749
Coefficient of variation (CV)	0.6049465369
Kurtosis	10.75107265
Mean	400.9368764
Median Absolute Deviation (MAD)	134.82
Skewness	0.04432815526
Sum	11959145.15
Variance	58828.25889
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-999	177	0.6%
333.79	6	< 0.1%
366.37	6	< 0.1%
185.9	5	< 0.1%
323.12	5	< 0.1%
430.93	5	< 0.1%
340.39	5	< 0.1%
408.45	4	< 0.1%
233.95	4	< 0.1%
400.66	4	< 0.1%
Other values (24031)	29607	98.7%
(Missing)	172	0.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-999	177	0.6%
33.76	1	< 0.1%
34.04	1	< 0.1%
39.61	1	< 0.1%
42.13	1	< 0.1%
43.09	1	< 0.1%
44.23	1	< 0.1%
44.63	1	< 0.1%
47.78	1	< 0.1%
48.2	1	< 0.1%

Value	Count	Frequency (%)
3840.88	1	< 0.1%
3419.66	1	< 0.1%
3025.4	1	< 0.1%
3018.15	1	< 0.1%
2512.02	1	< 0.1%
2481.22	1	< 0.1%
2052.85	1	< 0.1%
2035.34	1	< 0.1%
1995.57	1	< 0.1%
1993.87	1	< 0.1%

Expense Type 1
Boolean

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	29.4 KiB

False	19214
True	10786

Common Values
Chart

Value	Count	Frequency (%)
False	19214	64.0%
True	10786	36.0%

Expense Type 2
Boolean

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	29.4 KiB

True	20180
False	9820

Common Values
Chart

Value	Count	Frequency (%)
True	20180	67.3%
False	9820	32.7%

Dependents
Real number (ℝ_≥0)

MISSING

Distinct	10
Distinct (%)	< 0.1%
Missing	2493
Missing (%)	8.3%
Infinite	0
Infinite (%)	0.0%
Mean	2.253026502

Minimum	1
Maximum	14
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	2
Q3	3
95-th percentile	4
Maximum	14
Range	13
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.9511621081
Coefficient of variation (CV)	0.4221708476
Kurtosis	1.398534
Mean	2.253026502
Median Absolute Deviation (MAD)	1
Skewness	0.8047511637
Sum	61974
Variance	0.9047093559
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
2	13108	43.7%
3	5719	19.1%
1	5544	18.5%
4	2704	9.0%
5	372	1.2%
6	50	0.2%
7	7	< 0.1%
14	1	< 0.1%
10	1	< 0.1%
8	1	< 0.1%
(Missing)	2493	8.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	5544	18.5%
2	13108	43.7%
3	5719	19.1%
4	2704	9.0%
5	372	1.2%
6	50	0.2%
7	7	< 0.1%
8	1	< 0.1%
10	1	< 0.1%
14	1	< 0.1%

Value	Count	Frequency (%)
14	1	< 0.1%
10	1	< 0.1%
8	1	< 0.1%
7	7	< 0.1%
6	50	0.2%
5	372	1.2%
4	2704	9.0%
3	5719	19.1%
2	13108	43.7%
1	5544	18.5%

Credit Score
Real number (ℝ_≥0)

MISSING

Distinct	17586
Distinct (%)	62.1%
Missing	1703
Missing (%)	5.7%
Infinite	0
Infinite (%)	0.0%
Mean	739.8853811

Minimum	580
Maximum	896.26
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	580
5-th percentile	624.372
Q1	681.88
median	739.82
Q3	799.12
95-th percentile	854.78
Maximum	896.26
Range	316.26
Interquartile range (IQR)	117.24

Descriptive statistics

Standard deviation	72.1638461
Coefficient of variation (CV)	0.09753381799
Kurtosis	-0.9851944799
Mean	739.8853811
Median Absolute Deviation (MAD)	58.67
Skewness	-0.02025516921
Sum	20936536.63
Variance	5207.620684
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
792.76	9	< 0.1%
811.45	8	< 0.1%
844.26	7	< 0.1%
727.72	7	< 0.1%
777.86	7	< 0.1%
760.69	6	< 0.1%
782.9	6	< 0.1%
774.11	6	< 0.1%
735.8	6	< 0.1%
757.77	6	< 0.1%
Other values (17576)	28229	94.1%
(Missing)	1703	5.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
580	1	< 0.1%
580.85	1	< 0.1%
581.66	1	< 0.1%
582.3	1	< 0.1%
582.62	1	< 0.1%
583.05	2	< 0.1%
583.13	1	< 0.1%
583.34	1	< 0.1%
583.42	1	< 0.1%
583.54	1	< 0.1%

Value	Count	Frequency (%)
896.26	1	< 0.1%
892.18	1	< 0.1%
891.95	1	< 0.1%
891.75	1	< 0.1%
891.32	1	< 0.1%
890.02	1	< 0.1%
889.79	1	< 0.1%
889.72	1	< 0.1%
889.71	1	< 0.1%
889.24	2	< 0.1%

No. of Defaults
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

0	24182
1	5818

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	24182	80.6%
1	5818	19.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	24182	80.6%
1	5818	19.4%

Most occurring characters

Value	Count	Frequency (%)
0	24182	80.6%
1	5818	19.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	24182	80.6%
1	5818	19.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	24182	80.6%
1	5818	19.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	24182	80.6%
1	5818	19.4%

Has Active Credit Card
Categorical

MISSING

Distinct	3
Distinct (%)	< 0.1%
Missing	1566
Missing (%)	5.2%
Memory size	234.5 KiB

Active	9771
Inactive	9466
Unpossessed	9197

Length

Max length	11
Median length	8
Mean length	8.283076598
Min length	6

Characters and Unicode

Total characters	235521
Distinct characters	14
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Unpossessed
2nd row	Unpossessed
3rd row	Unpossessed
4th row	Active
5th row	Inactive

Common Values

Value	Count	Frequency (%)
Active	9771	32.6%
Inactive	9466	31.6%
Unpossessed	9197	30.7%
(Missing)	1566	5.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
active	9771	34.4%
inactive	9466	33.3%
unpossessed	9197	32.3%

Most occurring characters

Value	Count	Frequency (%)
e	37631	16.0%
s	36788	15.6%
c	19237	8.2%
t	19237	8.2%
i	19237	8.2%
v	19237	8.2%
n	18663	7.9%
A	9771	4.1%
I	9466	4.0%
a	9466	4.0%
Other values (4)	36788	15.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	207087	87.9%
Uppercase Letter	28434	12.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	37631	18.2%
s	36788	17.8%
c	19237	9.3%
t	19237	9.3%
i	19237	9.3%
v	19237	9.3%
n	18663	9.0%
a	9466	4.6%
p	9197	4.4%
o	9197	4.4%

Uppercase Letter

Value	Count	Frequency (%)
A	9771	34.4%
I	9466	33.3%
U	9197	32.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	235521	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	37631	16.0%
s	36788	15.6%
c	19237	8.2%
t	19237	8.2%
i	19237	8.2%
v	19237	8.2%
n	18663	7.9%
A	9771	4.1%
I	9466	4.0%
a	9466	4.0%
Other values (4)	36788	15.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	235521	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	37631	16.0%
s	36788	15.6%
c	19237	8.2%
t	19237	8.2%
i	19237	8.2%
v	19237	8.2%
n	18663	7.9%
A	9771	4.1%
I	9466	4.0%
a	9466	4.0%
Other values (4)	36788	15.6%

Property ID
Real number (ℝ_≥0)

Distinct	999
Distinct (%)	3.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	501.9347

Minimum	1
Maximum	999
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	1
5-th percentile	52
Q1	251
median	504
Q3	751
95-th percentile	949
Maximum	999
Range	998
Interquartile range (IQR)	500

Descriptive statistics

Standard deviation	288.1580858
Coefficient of variation (CV)	0.5740947693
Kurtosis	-1.202563661
Mean	501.9347
Median Absolute Deviation (MAD)	250
Skewness	-0.01051918972
Sum	15058041
Variance	83035.08241
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
839	51	0.2%
944	46	0.2%
102	46	0.2%
614	45	0.1%
787	45	0.1%
870	45	0.1%
278	44	0.1%
185	43	0.1%
768	43	0.1%
382	43	0.1%
Other values (989)	29549	98.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	32	0.1%
2	21	0.1%
3	28	0.1%
4	34	0.1%
5	30	0.1%
6	31	0.1%
7	26	0.1%
8	33	0.1%
9	26	0.1%
10	29	0.1%

Value	Count	Frequency (%)
999	26	0.1%
998	21	0.1%
997	29	0.1%
996	27	0.1%
995	28	0.1%
994	28	0.1%
993	32	0.1%
992	35	0.1%
991	36	0.1%
990	30	0.1%

Property Age
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	24179
Distinct (%)	96.1%
Missing	4850
Missing (%)	16.2%
Infinite	0
Infinite (%)	0.0%
Mean	2631.11944

Minimum	377.7
Maximum	1777460.21
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	234.5 KiB

Quantile statistics

Minimum	377.7
5-th percentile	1035.066
Q1	1650.45
median	2223.25
Q3	3091.4075
95-th percentile	5067.6665
Maximum	1777460.21
Range	1777082.51
Interquartile range (IQR)	1440.9575

Descriptive statistics

Standard deviation	11322.677
Coefficient of variation (CV)	4.303368684
Kurtosis	24008.67727
Mean	2631.11944
Median Absolute Deviation (MAD)	664.23
Skewness	153.2196101
Sum	66172653.91
Variance	128203014.5
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1608.43	4	< 0.1%
2415.7	4	< 0.1%
2104.26	3	< 0.1%
2412.07	3	< 0.1%
2114.52	3	< 0.1%
2052.94	3	< 0.1%
2304.81	3	< 0.1%
2013.11	3	< 0.1%
1946.61	3	< 0.1%
929.15	3	< 0.1%
Other values (24169)	25118	83.7%
(Missing)	4850	16.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
377.7	1	< 0.1%
378.76	1	< 0.1%
378.91	1	< 0.1%
393.09	1	< 0.1%
418.9	1	< 0.1%
424.45	1	< 0.1%
437.63	1	< 0.1%
438.44	1	< 0.1%
442.47	1	< 0.1%
450.16	1	< 0.1%

Value	Count	Frequency (%)
1777460.21	1	< 0.1%
122966.28	1	< 0.1%
54653.75	1	< 0.1%
48095.16	1	< 0.1%
32726.98	1	< 0.1%
31866.97	1	< 0.1%
31584.05	1	< 0.1%
28331.74	1	< 0.1%
27518.64	1	< 0.1%
26049.85	1	< 0.1%

Property Type
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

1	7863
2	7650
3	7309
4	7178

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	30000
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4
2nd row	2
3rd row	2
4th row	2
5th row	4

Common Values

Value	Count	Frequency (%)
1	7863	26.2%
2	7650	25.5%
3	7309	24.4%
4	7178	23.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	7863	26.2%
2	7650	25.5%
3	7309	24.4%
4	7178	23.9%

Most occurring characters

Value	Count	Frequency (%)
1	7863	26.2%
2	7650	25.5%
3	7309	24.4%
4	7178	23.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	7863	26.2%
2	7650	25.5%
3	7309	24.4%
4	7178	23.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	30000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	7863	26.2%
2	7650	25.5%
3	7309	24.4%
4	7178	23.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	7863	26.2%
2	7650	25.5%
3	7309	24.4%
4	7178	23.9%

Property Location
Categorical

MISSING

Distinct	3
Distinct (%)	< 0.1%
Missing	356
Missing (%)	1.2%
Memory size	234.5 KiB

Semi-Urban	10387
Rural	10041
Urban	9216

Length

Max length	10
Median length	5
Mean length	6.751956551
Min length	5

Characters and Unicode

Total characters	200155
Distinct characters	13
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Rural
2nd row	Rural
3rd row	Urban
4th row	Semi-Urban
5th row	Semi-Urban

Common Values

Value	Count	Frequency (%)
Semi-Urban	10387	34.6%
Rural	10041	33.5%
Urban	9216	30.7%
(Missing)	356	1.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
semi-urban	10387	35.0%
rural	10041	33.9%
urban	9216	31.1%

Most occurring characters

Value	Count	Frequency (%)
r	29644	14.8%
a	29644	14.8%
U	19603	9.8%
b	19603	9.8%
n	19603	9.8%
S	10387	5.2%
e	10387	5.2%
m	10387	5.2%
i	10387	5.2%
-	10387	5.2%
Other values (3)	30123	15.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	149737	74.8%
Uppercase Letter	40031	20.0%
Dash Punctuation	10387	5.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	29644	19.8%
a	29644	19.8%
b	19603	13.1%
n	19603	13.1%
e	10387	6.9%
m	10387	6.9%
i	10387	6.9%
u	10041	6.7%
l	10041	6.7%

Uppercase Letter

Value	Count	Frequency (%)
U	19603	49.0%
S	10387	25.9%
R	10041	25.1%

Dash Punctuation

Value	Count	Frequency (%)
-	10387	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	189768	94.8%
Common	10387	5.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	29644	15.6%
a	29644	15.6%
U	19603	10.3%
b	19603	10.3%
n	19603	10.3%
S	10387	5.5%
e	10387	5.5%
m	10387	5.5%
i	10387	5.5%
R	10041	5.3%
Other values (2)	20082	10.6%

Common

Value	Count	Frequency (%)
-	10387	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	200155	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	29644	14.8%
a	29644	14.8%
U	19603	9.8%
b	19603	9.8%
n	19603	9.8%
S	10387	5.2%
e	10387	5.2%
m	10387	5.2%
i	10387	5.2%
-	10387	5.2%
Other values (3)	30123	15.0%

Co-Applicant
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	234.5 KiB

1	25516
0	4316
-999	168

Length

Max length	4
Median length	1
Mean length	1.0168
Min length	1

Characters and Unicode

Total characters	30504
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	25516	85.1%
0	4316	14.4%
-999	168	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	25516	85.1%
0	4316	14.4%
999	168	0.6%

Most occurring characters

Value	Count	Frequency (%)
1	25516	83.6%
0	4316	14.1%
9	504	1.7%
-	168	0.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	30336	99.4%
Dash Punctuation	168	0.6%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	25516	84.1%
0	4316	14.2%
9	504	1.7%

Dash Punctuation

Value	Count	Frequency (%)
-	168	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	30504	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	25516	83.6%
0	4316	14.1%
9	504	1.7%
-	168	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	30504	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	25516	83.6%
0	4316	14.1%
9	504	1.7%
-	168	0.6%

Property Price
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	29632
Distinct (%)	98.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	131759.6803

Minimum	-999
Maximum	1077966.73
Zeros	0
Zeros (%)	0.0%
Negative	352
Negative (%)	1.2%
Memory size	234.5 KiB

Quantile statistics

Minimum	-999
5-th percentile	27945.385
Q1	60572.16
median	109993.61
Q3	178880.72
95-th percentile	315010.661
Maximum	1077966.73
Range	1078965.73
Interquartile range (IQR)	118308.56

Descriptive statistics

Standard deviation	93549.5481
Coefficient of variation (CV)	0.7100013291
Kurtosis	3.149422456
Mean	131759.6803
Median Absolute Deviation (MAD)	54675.335
Skewness	1.41696463
Sum	3952790408
Variance	8751517951
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-999	352	1.2%
85907.5	2	< 0.1%
51395.67	2	< 0.1%
356356.48	2	< 0.1%
335541.91	2	< 0.1%
51652.52	2	< 0.1%
77957.35	2	< 0.1%
28252.49	2	< 0.1%
57914.08	2	< 0.1%
53075.16	2	< 0.1%
Other values (29622)	29630	98.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-999	352	1.2%
7265.95	1	< 0.1%
7309.87	1	< 0.1%
7439.12	1	< 0.1%
7859.62	1	< 0.1%
7900.34	1	< 0.1%
8012.24	1	< 0.1%
8029.94	1	< 0.1%
8068.74	1	< 0.1%
8231.39	1	< 0.1%

Value	Count	Frequency (%)
1077966.73	1	< 0.1%
1028082.64	1	< 0.1%
987770.87	1	< 0.1%
769438.43	1	< 0.1%
736792.32	1	< 0.1%
683713.79	1	< 0.1%
680125.07	1	< 0.1%
678932.62	1	< 0.1%
674193.1	1	< 0.1%
667386.91	1	< 0.1%

Loan Sanction Amount (USD)
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct	21450
Distinct (%)	72.3%
Missing	340
Missing (%)	1.1%
Infinite	0
Infinite (%)	0.0%
Mean	47649.34221

Minimum	-999
Maximum	481907.32
Zeros	7865
Zeros (%)	26.2%
Negative	338
Negative (%)	1.1%
Memory size	234.5 KiB

Quantile statistics

Minimum	-999
5-th percentile	0
Q1	0
median	35209.395
Q3	74261.25
95-th percentile	141339.9685
Maximum	481907.32
Range	482906.32
Interquartile range (IQR)	74261.25

Descriptive statistics

Standard deviation	48221.14669
Coefficient of variation (CV)	1.01200026
Kurtosis	1.760122431
Mean	47649.34221
Median Absolute Deviation (MAD)	35209.395
Skewness	1.229939031
Sum	1413279490
Variance	2325278988
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	7865	26.2%
-999	338	1.1%
28937.45	3	< 0.1%
27394.93	2	< 0.1%
26047.92	2	< 0.1%
27767.18	2	< 0.1%
15270.22	2	< 0.1%
54850.85	2	< 0.1%
105047.72	2	< 0.1%
47136.42	2	< 0.1%
Other values (21440)	21440	71.5%
(Missing)	340	1.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-999	338	1.1%
0	7865	26.2%
4023.18	1	< 0.1%
4121.66	1	< 0.1%
4183.49	1	< 0.1%
4319.61	1	< 0.1%
4417.18	1	< 0.1%
4445.54	1	< 0.1%
4482.97	1	< 0.1%
4488.02	1	< 0.1%

Value	Count	Frequency (%)
481907.32	1	< 0.1%
395368.74	1	< 0.1%
326730.56	1	< 0.1%
323233.31	1	< 0.1%
313502.39	1	< 0.1%
313452.68	1	< 0.1%
301457.2	1	< 0.1%
293150.14	1	< 0.1%
292666.61	1	< 0.1%
289506.99	1	< 0.1%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Customer ID	Name	Gender	Age	Income (USD)	Income Stability	Profession	Type of Employment	Location	Loan Amount Request (USD)	Current Loan Expenses (USD)	Expense Type 1	Expense Type 2	Dependents	Credit Score	No. of Defaults	Has Active Credit Card	Property ID	Property Age	Property Type	Property Location	Co-Applicant	Property Price	Loan Sanction Amount (USD)
0	C-36995	Frederica Shealy	F	56	1933.05	Low	Working	Sales staff	Semi-Urban	72809.58	241.08	N	N	3.0	809.44	0	NaN	746	1933.05	4	Rural	1	119933.46	54607.18
1	C-33999	America Calderone	M	32	4952.91	Low	Working	NaN	Semi-Urban	46837.47	495.81	N	Y	1.0	780.40	0	Unpossessed	608	4952.91	2	Rural	1	54791.00	37469.98
2	C-3770	Rosetta Verne	F	65	988.19	High	Pensioner	NaN	Semi-Urban	45593.04	171.95	N	Y	1.0	833.15	0	Unpossessed	546	988.19	2	Urban	0	72440.58	36474.43
3	C-26480	Zoe Chitty	F	65	NaN	High	Pensioner	NaN	Rural	80057.92	298.54	N	Y	2.0	832.70	1	Unpossessed	890	NaN	2	Semi-Urban	1	121441.51	56040.54
4	C-23459	Afton Venema	F	31	2614.77	Low	Working	High skill tech staff	Semi-Urban	113858.89	491.41	N	Y	NaN	745.55	1	Active	715	2614.77	4	Semi-Urban	1	208567.91	74008.28
5	C-17688	Polly Crumpler	F	60	1234.92	Low	State servant	Secretaries	Rural	34434.72	181.48	N	N	2.0	684.12	1	Inactive	491	1234.92	2	Rural	1	43146.82	22382.57
6	C-23855	Nathalie Olivier	M	43	2361.56	Low	Working	Laborers	Semi-Urban	152561.34	697.67	Y	Y	2.0	637.29	0	Unpossessed	227	2361.56	1	Semi-Urban	1	221050.80	0.00
7	C-11006	Clarinda Montana	F	45	NaN	Low	State servant	Managers	Semi-Urban	240311.77	807.64	N	N	2.0	812.26	0	Active	314	NaN	2	Urban	1	401040.70	168218.24
8	C-26934	Kenny Ankrom	F	38	1296.07	Low	Working	Cooking staff	Rural	35141.99	155.95	N	Y	3.0	705.29	1	Active	241	1296.07	4	Rural	1	54903.44	22842.29
9	C-24944	Barbie Goetsch	M	18	1546.17	Low	Working	Laborers	Rural	42091.29	500.20	N	N	2.0	613.24	0	Unpossessed	883	1546.17	2	Urban	1	67993.43	0.00

Last rows

	Customer ID	Name	Gender	Age	Income (USD)	Income Stability	Profession	Type of Employment	Location	Loan Amount Request (USD)	Current Loan Expenses (USD)	Expense Type 1	Expense Type 2	Dependents	Credit Score	No. of Defaults	Has Active Credit Card	Property ID	Property Age	Property Type	Property Location	Co-Applicant	Property Price	Loan Sanction Amount (USD)
29990	C-49100	Chantel Costigan	F	64	4211.81	Low	Commercial associate	Cooking staff	Urban	225434.35	867.88	N	N	3.0	842.81	0	Unpossessed	408	4211.81	1	Urban	1	285966.63	0.00
29991	C-20609	Barbie Hice	F	55	NaN	Low	Commercial associate	High skill tech staff	Semi-Urban	127571.87	707.74	N	Y	2.0	NaN	0	Unpossessed	213	NaN	4	Urban	1	195998.69	95678.90
29992	C-32912	Nana Nell	M	34	2904.15	Low	Working	Laborers	Semi-Urban	141260.03	477.19	N	N	4.0	647.87	0	Inactive	922	2904.15	2	Semi-Urban	1	226298.50	0.00
29993	C-21440	Jonathon Rodriques	M	62	NaN	Low	Working	Cleaning staff	Semi-Urban	9811.65	107.88	N	N	2.0	709.43	1	Active	404	NaN	2	Urban	1	17956.31	6377.57
29994	C-7813	Jocelyn Deschamp	M	39	2250.19	Low	Commercial associate	Managers	Rural	83810.38	430.66	Y	Y	3.0	NaN	0	Inactive	265	2250.19	3	Urban	1	129028.33	62857.78
29995	C-43723	Angelyn Clevenger	M	38	4969.41	Low	Commercial associate	Managers	Urban	76657.90	722.34	Y	Y	2.0	869.61	0	Unpossessed	566	4969.41	4	Urban	1	111096.56	68992.11
29996	C-32511	Silas Slaugh	M	20	1606.88	Low	Working	Laborers	Semi-Urban	66595.14	253.04	N	N	3.0	729.41	0	Inactive	175	1606.88	3	Urban	1	73453.94	46616.60
29997	C-5192	Carmelo Lone	F	49	NaN	Low	Working	Sales staff	Urban	81410.08	583.11	N	Y	NaN	NaN	0	Active	959	NaN	1	Rural	1	102108.02	61057.56
29998	C-12172	Carolann Osby	M	38	2417.71	Low	Working	Security staff	Semi-Urban	142524.10	378.29	N	Y	3.0	677.27	1	Unpossessed	375	2417.71	4	Urban	1	168194.47	99766.87
29999	C-33003	Bridget Garibaldi	F	63	3068.24	High	Pensioner	NaN	Rural	156290.54	693.94	N	Y	1.0	815.44	0	Active	344	3068.24	3	Rural	1	194512.60	117217.90

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Uppercase Letter

Dash Punctuation

Most occurring scripts

Most frequent character per script

Common

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Lowercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category